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Abstract Bursty star formation—a key prediction for high-redshift galaxies from cosmological simulations explicitly resolving stellar feedback in the interstellar medium—has recently been observed to prevail among galaxies at redshiftz≳ 6. Line intensity mapping (LIM) of the 158μm [Cii] line as a star formation rate (SFR) indicator offers unique opportunities to tomographically constrain cosmic star formation at high redshift, in a way complementary to observations of individually detected galaxies. To understand the effects of bursty star formation on [Cii] LIM, which have remained unexplored in previous studies, we present an analytic modeling framework for high-zgalaxy formation and [Cii] LIM signals that accounts for bursty star formation histories induced by delayed supernova feedback. We use it to explore and characterize how bursty star formation can impact and thus complicate the interpretation of the [Cii] luminosity function and power spectrum. Our simple analytic model indicates that bursty star formation mainly affects low-mass galaxies by boosting their average SFR and [Cii] luminosity, and in the [Cii] power spectrum it can create a substantial excess in the large-scale clustering term. This distortion results in a power spectrum shape that cannot be explained by invoking a mass-independent logarithmic scatter. We conclude that burstiness must be accounted for when modeling and analyzing [Cii] data sets from the early Universe, and that in the extreme, the signature of burstiness may be detectable with first-generation experiments such as TIME, CONCERTO, and CCAT-DSS. 

Abstract The epoch of reionization (EoR) offers a unique window into the dawn of galaxy formation, through which high-redshift galaxies can be studied by observations of both themselves and their impact on the intergalactic medium. Line intensity mapping (LIM) promises to explore cosmic reionization and its driving sources by measuring intensity fluctuations of emission lines tracing the cosmic gas in varying phases. Using LIMFAST, a novel seminumerical tool designed to self-consistently simulate LIM signals of multiple EoR probes, we investigate how building blocks of galaxy formation and evolution theory, such as feedback-regulated star formation and chemical enrichment, might be studied with multitracer LIM during the EoR. On galaxy scales, we show that the star formation law and the feedback associated with star formation can be indicated by both the shape and redshift evolution of LIM power spectra. For a baseline model of metal production that traces star formation, we find that lines highly sensitive to metallicity are generally better probes of galaxy formation models. On larger scales, we demonstrate that inferring ionized bubble sizes from cross-correlations between tracers of ionized and neutral gas requires a detailed understanding of the astrophysics that shape the line luminosity–halo mass relation. Despite various modeling and observational challenges, wide-area, multitracer LIM surveys will provide important high-redshift tests for the fundamentals of galaxy formation theory, especially the interplay between star formation and feedback by accessing statistically the entire low-mass population of galaxies as ideal laboratories, complementary to upcoming surveys of individual sources by new-generation telescopes. 

ABSTRACT We present the joint analysis of Neutral Hydrogen (H i) Intensity Mapping observations with three galaxy samples: the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples from the eBOSS survey, and the WiggleZ Dark Energy Survey sample. The H i intensity maps are Green Bank Telescope observations of the redshifted $$21\rm cm$$ emission on $$100 \, {\rm deg}^2$$ covering the redshift range 0.6 < z < 1.0. We process the data by separating and removing the foregrounds present in the radio frequencies with FastI ICA. We verify the quality of the foreground separation with mock realizations, and construct a transfer function to correct for the effects of foreground removal on the H i signal. We cross-correlate the cleaned H i data with the galaxy samples and study the overall amplitude as well as the scale dependence of the power spectrum. We also qualitatively compare our findings with the predictions by a semianalytical galaxy evolution simulation. The cross-correlations constrain the quantity $$\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm opt}}$$ at an effective scale keff, where $$\Omega _\rm {H\,\small {I}}$$ is the H  i density fraction, $$b_\rm {H\,\small {I}}$$ is the H i bias, and $$r_{\rm {H\,\small {I}},{\rm opt}}$$ the galaxy–hydrogen correlation coefficient, which is dependent on the H  i content of the optical galaxy sample. At $$k_{\rm eff}=0.31 \, h\,{\rm Mpc^{-1}}$$ we find $$\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm Wig}} = [0.58 \pm 0.09 \, {\rm (stat) \pm 0.05 \, {\rm (sys)}}] \times 10^{-3}$$ for GBT-WiggleZ, $$\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm ELG}} = [0.40 \pm 0.09 \, {\rm (stat) \pm 0.04 \, {\rm (sys)}}] \times 10^{-3}$$ for GBT-ELG, and $$\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm LRG}} = [0.35 \pm 0.08 \, {\rm (stat) \pm 0.03 \, {\rm (sys)}}] \times 10^{-3}$$ for GBT-LRG, at z ≃ 0.8. We also report results at $$k_{\rm eff}=0.24$$ and $$k_{\rm eff}=0.48 \, h\,{\rm Mpc^{-1}}$$. With little information on H i parameters beyond our local Universe, these are amongst the most precise constraints on neutral hydrogen density fluctuations in an underexplored redshift range. 

Abstract We introduce DAYENU, a linear, spectral filter for HI intensity mapping that achieves the desirable foreground mitigation and error minimization properties of inverse co-variance weighting with minimal modeling of the underlying data. Beyond 21 cm power-spectrum estimation, our filter is suitable for any analysis where high dynamic-range removal of spectrally smooth foregrounds in irregularly (or regularly) sampled data is required, something required by many other intensity mapping techniques. Our filtering matrix is diagonalized by Discrete Prolate Spheroidal Sequences which are an optimal basis to model band-limited foregrounds in 21 cm intensity mapping experiments in the sense that they maximally concentrate power within a finite region of Fourier space. We show that DAYENU enables the access of large-scale line-of-sight modes that are inaccessible to tapered DFT estimators. Since these modes have the largest SNRs, DAYENU significantly increases the sensitivity of 21 cm analyses over tapered Fourier transforms. Slight modifications allow us to use DAYENU as a linear replacement for iterative delay CLEANing (DAYENUREST). We refer readers to the Code section at the end of this paper for links to examples and code.